The Four Types of Memory for AI Agents (and How Claude Code Implements Each)

TLDR Memory is what separates a chatbot from an agent. A chatbot answers. An agent answers shaped by what it knows about your project and what it learned last time. There’s a clean framework for this from a Princeton team called CoALA, and it splits agent memory into four types: working, semantic, procedural, episodic. This post defines all four in general, then shows how Claude Code implements each one as something you can point at on disk. Claude Code maps every type to plain files and commands, not a vector database. The most interesting frontier is episodic memory and consolidation, the thing Anthropic calls “dreaming.” Match the memory to the job. A thermostat needs one type. A coding agent wants all four. Why I care about agent memory I don’t write much code by hand anymore. I delegate to a coding agent and review the output. And the thing that decides whether that delegation is great or painful isn’t the model’s raw IQ, it’s what the agent remembers. Two failure modes I hit…